Embedded Development Platforms To Design Prototypes Of ... · Texas Instrument‟s Beaglebone Black, Intel Galileo, XBEE® as well as some industry grade platforms like cypress Semiconductor‟s

International Journal of Research in Advent Technology, Vol.7, No.4, April 2019

E-ISSN: 2321-9637

Available online at www.ijrat.org

344

Embedded Development Platforms To Design Prototypes Of

Internet Of Things (Iot) Applications: A Study

Ayaskanta Mishra1

Assistant Professor, School of Electronics Engineering1, Kalinga Institute of Industrial Technology (KIIT) Deemed to be

University, Bhubaneswar, Odisha, India1

Email: [email protected]

Abstract- In this paper a comprehensive study of different development platforms for Internet of Things (IoT) application are

surveyed and a comparative analysis is presented. This paper reviews diverse spectrum of development platforms and a

comparative analysis of different technical aspects is discussed. The major focus of this review paper is to give a quantitative

analysis of embedded platforms with bare metal and Linux environment and their network connectivity to cloud analytics

platforms. This review has considered some popular prototyping platforms like: Arduino UNO, Node MCU, Raspberry Pi3,

Texas Instrument‟s Beaglebone Black, Intel Galileo, XBEE® as well as some industry grade platforms like cypress

Semiconductor‟s PSoC4 BLE and microchip‟s SoC PIC32 and SAM series embedded platforms. Comparative analysis is

based on technical specifications, computation power, cost, reliability, learning curve and time to market.

Keywords- IoT; prototyping; Arduino; NodeMCU; Raspberry Pi; Intel Galileo; XBee; PSoC; PIC32

1. INTRODUCTION

Internet of Things (IoT) is interconnection of cyber-

physical objects for seamless data acquisition from sensors

and at the same time controlling actuators and driving motors

for any mechanical actions in physical space. The

interconnections for such smart objects are done over a

generic global network or “Internet”. For enabling the

decision making based on the data collected from cyber

physical objects of human users the database and computing

can be done in cloud or a server deployed in the internet.

Communication aspect of IoT is taken care by the TCP/IP

protocol stack, which is the backbone of Internet. As

discussed in this context; smarter cyber physical objects like

sensors, motors or actuators can be interfaced with intelligent

devices or motes which are seamlessly connected through

internet. In this paper, a comprehensive review has been

done on various such popular development platforms

prototyping of any IoT applications.

Developing an IoT application requires four major

building blocks namely 1) Sensors and Actuators 2) MCU

MPU Development boards 3) Network and protocols 4)

Cloud and data analytics. These can be referred as four

pillars of IoT. These four pillars of IoT can be described as

given in figure 1. “Sensors” are Transducers, which converts

physical parameters like Temperature, Pressure, Humidity,

and Gas Concentration into Electrical parameters like

Voltage/ Current. The physical movement is handled by a

machine component called Actuator. Actuators requires two

types inputs one is control input, which is relatively low

power and the second one is the power input, provides the

required energy to operate. The second one can be electric

voltage or current, pneumatic or hydraulic pressure, or

human power. A microprocessor is the computation engine -

CPU (central processing unit) that is fabricated on a single

chip. Microcontrollers are low power devices specially

housing CPU, Memory and I/O in single chip especially

designed for interfacing application or single chip computer.

System on Chip (SoC) is modern approach to develop the

whole computer system on a single chip including network

adaptor except the power circuit and antenna outside the

chip. Many modern prototyping platforms like Raspberry Pi,

Intel Galileo, Cypress PSoC4 and Microchip platforms use

above SoC technology.

Network and protocol for IoT can be application specific

it depends on communication requirement of the IoT

application.WAN, LAN and PAN networks can be used for

IoT depending upon range, data-rate and power constraints.

For long range applications LoRaWAN is the latest and

gaining a lot of popularity. Apart for this conventional WAN

like LTE, GSM, GPRS can be used. In case of LAN both

IEEE 802.3 Ethernet for wired applications and IEEE 802.11

WLAN for wireless application can be used. For power

constraint applications with limited range WPAN

technologies like Bluetooth, BLE and Zigbee can be used

based on application requirements. The final building block

is the cloud which is nothing but an Internet Server for

database as well as analytics and visualization of data and

application preferably on a web interface GUI. Various

protocols are supported for such application layer servers

like HTTP, MQTT and CoAP.

This paper is organized in five chapters. Section 1

describes the introduction to IoT prototyping aspects. Section

2 reviews various prototyping development platforms.

Section 3 shows the comparative analysis. Section 4 gives a

recommendation for selecting appropriate platforms for

Fig.1: Four pillars of IoT

Sensors &

Actuators

Processors/ Controllers

Development Boards

Network / Protocol

Cloud &

Data Analytics


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developing IoT applications based on specific scenarios.

Finally Section 5 concludes the paper.

2. A REVIEW ON IOT DEVELOPMENT

PLATFORMS

Developing an IoT application requires a smart motes or

nodes. These smart devices have some computational

intelligence. Such nodes can be programmed and interfaces

with various sensors as well as actuators. These nodes can

be interconnected using Internet enabled by TCP/IP protocol

stack and connected to a centralized cloud server for various

application specific scenarios. For developing and

prototyping such smart embedded devices various industry

standard development boards can be used. The following are

some standard and popular embedded system prototyping

platforms for development of IoT applications. A detailed

comparison of Arduino [1], raspberry pi and ESP8266 is

presented by authors [2].

2.1. Arduino UNO

Arduino UNO is a popular embedded platform with an

added feature of being open source. Arduino is an

ATmega328 8-bit 20 MHz micro controller at its core.

Arduino is a very low end platform in terms of technical

specifications for developing IoT applications prototypes.

Figure 2 shows a Arduino UNO R3 Board.

Arduino is at the top position in terms of popularity

mostly because of it is easy to learn and use. In addition to

that a lot of online resource and support forms and

communities are available for Arduino. Arduino has its own

software development platform called Arduino IDE and „C‟

programming is used with void setup() and void loop() two

main program structure.

2.2. Node MCU

Espressif Systems has developed a firmware of ESP

family. Authors have presented a literature [3]. There are

many Wireless LAN modules in this family namely ESP-01,

ESP-12 etc. NodeMCU is based on the ESP8266 Wireless

LAN (IEEE 802.11) firmware. Since its inception

NodeMCU has gained a lot of popularity among developers

because of two major reasons: firstly it is ESP-12 based

device having very small form factor with inbuilt Wi-Fi and

secondly it has good software support with LUA scripting

language and Arduino IDE based c programming support.

[3] LUA scripting language support for NodeMCU is from

eLUA project and built on Espressif Non-OS SDK for

ESP8266. Various open source projects like lua-cjson and

spiffs are some added advantage of NodeMCU. Figure 3

shows a NodeMCU module. The technical specifications are

given in Espressif literature [4].

2.3. Raspberry Pi

Raspberry Pi is a credit card size single board computer.

Unlike above two discussed embedded platform Raspberry

Pi is a full-fledged minicomputer with all the standard

peripheral of a PC. A review has been presented by authors

in their paper [5]. Latest Raspberry Pi has four USB ports

which support all standard peripherals like keyboard, mouse,

modems and dongles. In addition to that it has a HDMI port

for connecting to display device like Monitor or TV.

Raspberry Pi 3 Model B+ is powered by a Broadcom SoC

with clock speed of 700 MHz to 1.4 GHz; on-board memory

ranges from 256 MB to 1 GB RAM. Figure 4 shows a

Raspberry Pi3 Single board Computer. A comparative

analysis of technologies is presented in paper [6]. Power

consumption of raspberry pi is presented in literature [7].

The operating system and program memory are stored in

Secure Digital (SD) card in either SDHC (early Raspberry

Pi's) or MicroSDHC (Later Raspberry Pi's) sizes. The SoC is

ARM based and house both CPU and GPU for processing.

The latest Raspberry Pi has inbuilt Wi-Fi (IEEE 802.11) as

well as Bluetooth 4.0 (IEEE 802.15.1) with Bluetooth Low

Energy (BLE) support. Raspberry Pi also has extensive 40

pins General purpose input output (GPIO) with UART, SPI

and I2C support. In addition to all these it has a 3.5 mm

audio jack for audio and signal processing applications.

Prices of Raspberry Pis range from US$5 to $35. Pi works

on a Linux based OS platforms. Python is the most popular

language for Raspberry pi developers, though Pi can support

mostly all kind of programming language as it is a Linux

based minicomputer. A case study of Restful framework in

Raspberry Pi performance and energy overview is presented

in the paper [8].

Fig.2: Arduino UNO R3 prototyping board

Fig. 3: NodeMCU prototyping board with Espressif

ESP8266 Wi-Fi SoC

Fig. 4: Raspberry Pi 3 prototyping board with Broadcom

SoC


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2.4. BeagleBone Black

Texas Instruments is a key player in embedded

development platform. The latest version of BeagleBone

series is BeagleBone Black. The BeagleBone is an open

source platform for prototyping of IoT applications. The

platform has a added advantage of being low-cost and low-

power. The BeagleBone Series is a venture by joint

collaboration between TI, Digi-Key and element14. The

BeagleBone is a single-board computer. Texas Instrument's

OMAP3530 system-on-a-chip is the core of BeagleBone

boards. Figure 5 shows a Texas Instruments BeagleBone

Black Single board Computer. The book has a excellent

discussion of various aspect of BeagleBone Black [9].

The platform supports open source software development

for scenario specific IoT application prototyping and

development.

Texas Instrument‟s ARM Cortex A8 based Sitara

XAM3359AZCZ100 processor is a lower-cost, high-

expansion SoC being used in BeagleBone boards. Sitara base

BeagleBone boards are analogous to the BeagleBone Black

however some features are tweaked, which are more relevant

to modern age application development. A review on

BeagleBone is presented in the paper [10].

2.5. Intel® Galileo Gen2

Intel® also has a product in IoT prototyping market

called Intel® Galileo Family namely Gen1 and Gen2. The

latest one being Galileo Gen2. Authors of [11] have

presented a review on Intel Galileo. The Galileo is based on

Intel x86 architecture and it is first in line of Arduino-

certified development boards. This board is developed by

Intel keeping the research & academia in mind. The Galileo

boards are popularly referred in the community as “Breakout

boards”. The main features of Intel Galileo boards are low-

power and small-core. The Galileo boards are powered by

Intel® Quark SoC X1000 the first product from Intel Quark

family. This product is developed in Ireland to compete

within Internet of Things market segment especially edge

nodes of clouds to facilitate applications like smart wearable

computing devices. Some key technical specifications of

Quark SoC X1000 are 32-bit, Single-core, single-thread,

Pentium (P54C/i586) architecture. Quark is an instruction set

architecture (ISA) compatible CPU. The operating clock

frequency is up to 400 MHz. Quark SoC is a counterpart

from Intel® to the ARM based platform which is typically

very popular in smart phones and other single-board

computers. Author has presented an experimental analysis on

Galileo for IoT [12]. The author of [13] has presented

Galileo for beginners. Figure 6 shows an Intel® Galileo

Gen2 development board.

The Galileo is more powerful when it comes to system

specifications. A clock speed of 400MHz equipped with 256

MB of DDR3 RAM and 8 MB flash memory. The Galileo

can outperform any Arduino device when it comes to

computing. The Arduino platform are quite low end platform

for an example, Arduino Mega is mere 16 MHz, 8 KB RAM

and 256 KB flash memory. Rather Intel® Galileo boards are

more comparable with other Single board computer

platforms like Raspberry Pi Family or BeagleBone family.

The author of [14] has given the technical details on Galileo.

Raspberry Pi based devices are more powerful than the

Galileo Series however RPi lacks in one front only that it

does not have any flash memory rather has a SD Card/

MicroSD card slot for OS and Program memory

requirements. Intel® Galileo support Linux OS based yocto

distributions. There are some useful resources available by

various authors. The author of [15] has given a starter‟s

guide for Galileo, [16] has written on programming aspects

of Galileo and [17] has presented on essentials of Galileo.

2.6. Digi XBee®

Digi XBee radio modules are for LR-WPAN applications

mostly used for low power Wireless Sensor Networks. XBee

got its name from Zigbee (IEEE 802.15.4). The authors of

[18] have presented Wireless Sensing using XBee. First

lunched in 2005 by MaxStream brand is based on IEEE

802.15.4-2003 standard. XBee modules are designed as

point-to-point and works on star topology with baud rates of

250 kbps. There are two types of models for XBee. Authors

of [19] have presented a review on XBee. First one is cheap

1mW low power modules and second one is 100 mW XBee-

PRO modules. As the number of XBee deployment grows

new ecosystem of XBee gateways, adaptors and software has

evolved. XBee radio modules are low power and used mostly

in a Mesh scenario for low data rate sensor applications.

Authors have presented a research article on WSN using

ARM [20]. The common features of XBee modules are

UART, Power management, flow control, Digital I/O and

Analog to Digital Converter (ADC) built in. Field

performance analysis IEEE 802.15.4 XBee is presented in

[21]. Performance analysis of XBee based WSN is presented

in [22]. Wireless Mesh Networking with XBee is presented

by authors in [23].

Fig.5: TI‟s BeagleBone Black with ARM Cortex A8

Fig.6: Intel Galileo Gen2 development board with Intel

Quark X1000 SoC


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The programmable XBee have an additional on-board

processor for user‟s code. The programmable XBee and a

surface-mount version of the XBee radios were both

introduced in 2010. XBee support XCTU software

framework and Zigbee packet can be captured through

UART. Figure 7 shows XBee radio module. Application of

Zigbee compatible XBee and XBeePro is presented in paper

[24]. Design of WSN based on Zigbee is presented by author

in [25].

2.7. Cypress PsoC4 BLE

Cypress CY8CKIT-143A PSOC® 4 Bluetooth Low

Energy Pioneer Kit 256K Kit provides designers certified

45x27x2mm, easy-to-use solution for creating a complete

Bluetooth® Low Energy (BLE) system. The Kit consists of

PsoC 4 Bluetooth Low Energy device with internal flash of

256KB, 24MHz and 32.768 kHz crystals, a PCB antenna,

and other passives. The CY8CKIT-143A provides easy

access to all GPIOs on the device. This Io Development Kit

is very easy to use; designers can either plug the module into

the CY8CKIT-042-BLE Kit or use the module with

CY8CKIT-002 MiniProg3 (an external programmer not

included in Kit). PSoC creator is the software to design

embedded application for Cypress SoCs. Figure 8 shows the

CY8CKIT-143A PSOC® 4 BLE Module. Power

consumption analysis of Bluetooth Low Energy product is

presented in the research work in [26]. A security system

design using BLE is presented in [27]. Authors have

presented experimental characterization of low power device

for IoT applications in [28].

2.8. Microchip PIC32 curiosity IoT development board

Microchip PIC32 curiosity IoT Development board from

Microchip Technology is for developing Amazon

FreeRTOS-based applications. The Amazon FreeRTOS

Curiosity PIC32MZ EF Bundle DM320104-BNDL has a

Curiosity PIC32MZ EF IoT development board, a Wi-Fi

board and an USB UART click board that is used for

developing an AWS cloud-connected application. An ultra

low power digital architecture for IoT is presented by authors

in their research [29]. This bundle includes a LAN8720A

PHY daughter board to create Ethernet-connected

applications. Authors have presented a programming aspect

of PIC32 in [30].

Amazon FreeRTOS is a microcontroller operating system

that makes small, low-powered edge devices. This bundle

makes it easy for designers to develop, deploy, secure, and

maintain IoT Applications. Amazon FreeRTOS is popular

open source operating system based on FreeRTOS, for

microcontrollers, and includes inbuilt software libraries to

securely connect devices locally to AWS Greengrass, and

directly to the cloud, and update remotely. The high-

performance PIC32MZ EF MCUs host the Amazon

FreeRTOS and run at up to 415 DMIPs with industry-leading

connectivity options including 10/100 Ethernet MAC, Dual

CAN and Hi-Speed USB, ample Flash memory of up to 2

MB, rich peripherals, and a robust tool chain which empower

embedded designers to build complex applications rapidly.

Figure 9 shows the Microchip PIC32 curiosity development

board. The authors have presented embedded computing and

mechatronics using PIC32 in [31]. Further a design of secure

and energy efficient embedded system for future Internet

applications is presented in [32].

2.9. Microchip SAM Series IoT Dev Kit

Microchip Zero Touch Secure Provisioning Kit is an IoT

development Dev Kit that helps designer to develop quick

and secure IoT devices those are complaint with the AWS

security regulations. AWS has a strict mutual authentication

requirement between device and the remote servers of AWS

cloud. A robust authentication must be in place to ensure a

complete safe guarding of system credentials such as private

keys from the application core to avoid leaving backdoors

opened to software loop holes. In addition, the software is as

secure as the user‟s skill set is in security. Human users and

software can often be one of the easiest targets for a hacker

as they are the least reliable elements. Incorporating

Microchip pre-configured ATECC508-MAHAW or

ATECC508ASSHAW Crypto Authentication devices into a

system is a very secure method to connect to the AWS IoT

service. It leaves the whole handling of certificate and

private key manipulation to Microchip secure provisioning

factories in addition to keeping credentials away from

software and users. The ATECC508A and ATECC608A

devices in the kit are generic devices. Starting with the

upgraded Zero Touch Provisioning Kit for AWS IoT Version

B and benefit from the new configuration and provisioning

scripts (Python based) and AWS IoT account configuration

Fig.7: Digi XBee IEEE 802.15.4 form factor compatible radio

modules

Fig.8: Cypress CY8CKIT-143A PSOC® 4 BLE Module

Fig.9: Microchip PIC32 curiosity IoT development board

with 32-bit MCU


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scripts (using Cloud formation). Figure 10 shows Microchip

IoT development kit with hardware cryptography and AWS

cloud support. Microchip product specifications as given in

company web resource [33].

This version B of the kit comes with an easier on

boarding process to generate certificates and provision them

into the Crypto Authentication device using Python scripts.

In addition, the user will have access to a Cloud Formation

script to generate a web UI reflecting the I/O of the kit and

utilize it as a foundation to develop virtually any sensor

based use cases. In addition to the ATECC508A and

ATECC608A devices, the kit includes a Cortex-M4

ATSAMG55 and Wi-Fi ATWINC1500 using FreeRTOS and

the ATWINC1500 integrated TLS stack. The IoT

development kit can be programmed using c language using

the ATMEL studio. This is the latest SAM series product

from ATMEL after the acquisition by Microchip. The

authors have presented a study on efficient power

consumption wireless communication techniques for IoT

application in [34].

3. COMPARATIVE ANALYSIS

In chapter 2, we have seen nine popular IoT prototyping

development platforms in brief. In this chapter a

comparative analysis is done based on seven aspects of IoT

application prototyping. First one being the comparison of

technical specifications of all the above discussed

development platforms. In the later part of the chapter we

can see the comparison of these nine development platforms

based on computational power, cost, reliability, learning

curve, OS support and programmability and time to market.

3.1. Technical Specification

The comparison of technical specifications is done based

on CPU, RAM, Memory, I/O, Network Connectivity, OS

and programming aspects of the all the above mentioned

nine IoT application development platforms.

3.2. Computational power

The following Figure.11 shows the comparative analysis

of the computational power of the mentioned IoT

development platforms in scale of relative grading based on

CPU, RAM. .

Fig.10: Microchip IoT Development kit with hardware

cryptography and AWS support

Fig. 11 Computational Power of IoT development platforms


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Table 1. Technical Specification

Platform CPU/MCU/SoC RAM Memory I/O Network

Connectivity

OS/

Programming

Arduino ATmega328 8-bit 20

MHz

2KB Flash

Memory

32KB,

EEPROM

1KB

DIO: 14 with 6

PWM, Analog: 6,

I2C, SPI,UART

External Shield

WLAN, BLE,

WAN

Bootstrap/

Arduino IDE

NodeMCU Xtensa® 32-bit 80

MHz

160KB Flash

Memory

16MB

GPIO: 17, 8 PWM,

I2C, ADC:10 bits,

SPI, UART

WLAN 802.11

b/g/n HT

ESP8266

inbuilt

XTOS/

Arduino IDE

C++, Lua, lua-

cjson, and

spiffs

Raspberry Pi

3*

Broadcom BCM2837.

4× ARM Cortex-A53,

1.2GHz. GPU:

BroadcomVideoCoreIV

1GB

LPDDR2

(900

MHz)

MicroSD 40-pin header,

populated, I2C,

SPI,UART, USB

10/100Ethernet,

WLAN802.11n,

Bluetooth 4.1,

BLE

Linux,

Raspbian/

C++, Python,

Java…

BeagleBone

Black

TI DM3730 Processor -

1 GHz ARM Cortex-A8

core. PowerVR SGX

2D/3D graphics

processor

512 MB

LPDDR

RAM

MicroSD 4xUART, 8×

PWM, LCD,

GPMC, MMC1, 2×

SPI, 2× I²C, A/D

Converter,

2× CAN Bus,

4× Timers

10/100 Ethernet

IEEE 802.11n

(WLAN

Version)

Linux,

Android,

Windows,

Embedded/ C,

C++, Python,

Perl, Ruby,

Java, Shell

Script

Intel Galileo

Gen2

Intel Quark SoC x1000

400 MHz

256 MB

DDR3

RAM

Flash

Memory

8M,

EEPROM

8 kb,

Micro SD

card slot

up to

32GB

DIO: 20 with 6

PWM, Analog: 6,

I2C, SPI,UART,

USB host & client

10/100

Ethernet,

External: Intel

Centurion Wi-

Fi 802.11 b/g/n

Yocto 1.4

Poky Linux/

Arduino IDE

C++, python,

Nodejs, js

XBee® EM357 32-bit ARM®

Cortex -M3 processor

Operation at 6, 12, or

24 MHz

12 KB

RAM

128 or

192 kB

flash

Memory

DIO 0-8 PWM 0-1

ADC AD 0-5

UART, SPI

IEEE 802.15.4

6LoWPAN

Bootstrap/AT

Mode, API

Mode UART

CypressPSoC4

BLE

PSoC 4 BLE is an 32-

bits ARM® Cortex®-

M0 48MHz PSoC 4200

32

KB/16

KB

SRAM

256

KB/128

KB Flash

GPIO 3 Ports up to

98 I/O, ADC

12bits, 4 UART, 8

PWM

Bluetooth 4.1 Bootstrap/

PSoC Creator

Embedded C

Microchip

PIC32 MZ

curiosity

PIC32MZ2048EFM100

32-bit MCU:

200MHz

512KB

SRAM

2MB

Flash

Integrated FPU &

Crypto

accelerator,Hi-

Speed USB

LAN8720A:

10/100 Ethernet

Transceiver &

CAN

ATWINC1500

IoT network

controller:

IEEE 802.11

b/g/n Single-

band 2.4GHz

FreeRTOS/

MPLAB

Embedded C

Platform CPU/MCU/SoC RAM Memory I/O Network

Connectivity

OS/

Programming

Microchip ATSAMG55 32-bit 176 KB 512 KB Two PIO ATWINC1500 Bare metal/


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SAM IoT Dev

kit

ARM® Cortex®-M4

120MHz (Complete

development and

prototyping platform on

AWS IoT service

Includes three

CryptoAuthed Xplained

Pro Rev B

(ATCRYPTOAUTH-

XPRO-B) add-on

boards, with

ATECC508A and

ATECC608A.)

SRAM Flash Controllers provide

control of up to 48

I/O lines, One 8-

channel ADC,

resolution up to 12

bits, SPI, USART,

USB

IoT network

controller:

IEEE 802.11

b/g/n Single-

band 2.4GHz

Atmel Studio 7

Embedded C

Raspberry Pi 3 is the latest hardware # All the specification collected from official source

3.3. Cost


of the cost in $ USD of the mentioned IoT development

platforms.

3.4. Reliability


of the reliability of the mentioned IoT development

platforms. Reliability index is the measure of stability of

system over an IoT deployment and service provisioning.

This factor depends up on the device built quality as well as

the type of programming or stack used in the device.

3.5. Learning Curve


of the learning curve of the mentioned IoT development

platforms. Learning curve is the difficult level in getting

technical expertise to develop IoT products in the platform.

3.6. OS support & Programmability


of the OS support & Programmability of the mentioned IoT

development platforms. This gives an idea that how well

supported the particular platform is. Some platform support

only firmware level programming at the same time some

platform support bare metal as well as Linux or RTOS.

This OS support also affect the overall system

programmability factor as a full-fledged Linux OS can

support a wide range of programming language.

3.7. Time to market


of the Time to market of the mentioned IoT development

platforms. Time to market is the factor which is crucial for

developing a IoT application. The stiffer will be the learning

curve and more complex would be the development platform

more time it will take to develop an application on that

platform.

Fig. 12 Cost in $ USD of IoT development platforms

Fig.13: Reliability Index of IoT development platforms

Fig.14: Learning curve of IoT development platforms

Fig.15: OS Support and programmability of IoT development

platforms


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4. RECOMMENDATIONS FOR IOT APPLICATION

PROTOTYPING

Based on the comparative analysis given in Chapter III,

we can draw some inference and a recommendation can be

drafted. In case the IoT application is a basic one which does

not require any specific industrial demand Arduino or

NodeMCU can be used both are very less learning curve and

time to market. A very easy prototyping can be done using

Arduino using required shield based on the application

requirements. In case the application requires a very high

computational requirement like deployment of a cloud server

of MQTT broker to be deployed then Raspberry Pi 3 is the

best option. Other development boards like TI‟s BeagleBone

Black or Intel® Galileo Gen2 can also be used for such

complex applications. All these platforms give a very good

Linux OS support and very rich set of programming library

support for complex and computationally power hungry

applications. If the IoT prototyping requirements involves a

very high duty cycle or high reliability ideally for everyday

deployment scenario then industry grade MMRP based

embedded platforms like Cypress PSoC4 BLE, Microchip

PIC32 or SAMG55 based IoT dev kit can be used for best

service.

IoT is not a technology by itself rather a technology

framework for interconnected smart objects and devices over

internet enabled by various modern days technologies. Toda‟s

IoT industry takes the technological advantages of multi-

disciplinary research in the fields of industrial instrumentation

(sensors and actuators), VLSI, Embedded systems,

networking and Internet technologies. Further IoT industry

gets fuelled by the latest advancement in the field of cloud-

computing platforms. The extensive use of tools likes

Machine learning and Artificial Intelligence is aiding the IoT

industry multi folds in recent times. Figure 17 depicts a

generic IoT architecture for modern applications. Point to be

noted here the architecture remain unchanged in most of the

scenario only the building blocks can be customized based of

scenario specific requirements. A heterogeneous IoT

application framework is presented in the paper [35].

5. CONCLUSION

The review can be concluded with a endnote that, the

selection of IoT prototyping development platform can be

completely based on application specific requirement. No

particular embedded development platform is best or worst. It

is the application, which makes it best suitable. The previous

section has given some recommendations based on which a

particular development platform can be selected and an IoT

application prototyping can be provisioned to the end user.

The Arduino family is best suitable for low duty cycle

applications with not much demand on computational

resources (8-bit 20 MHz MCU) having very easy to learn and

user friendly development environment with lot of online

resource available. Arduino UNO is low cost under $10 with

lower reliability score of 7 in this review. Arduino UNO

lacks in one aspect that, it requires external shield or Wireless

Modules to be connected to cloud for IoT applications.

NodeMCU is close competitor to Arduino UNO with better

programming options as it supports both Arduino IDE and

LUA scripting. In this review having a 32-bit 80MHz MCU

is having a computational power almost four times of

Arduino UNO. However XBEE® is a whole new platform

especially for Wireless Sensor Network deployment with

IEEE 802.15.4 Zigbee technology. XBEE® is best suitable

Fig.16: Time to market of IoT development platforms

Fig.17: Generic Architecture of Internet of Things for modern day‟s applications


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for low power sensor network application with complete

support of mesh networking. XBEE® is based on a 32-bit

ARM® Cortex -M3 MCU up to 24MHz. XBEE® is having a

better reliability index of 9, which is more than Arduino as

well as NodeMCU in this review.

Unlike the above three development boards the Cypress

PSoC4 BLE is based on a 32-bits ARM® Cortex®-M0

48MHz MCU support industry grade product with support

for Memory Mapped Register Programming (MMRP).

Microchip SAM IoT kit is powered by a 32-bit ARM®

Cortex®-M4 120MHz MCU where as Microchip PIC32 is

powered by a 32-bit MCU 200MHz. Cypress and Microchip

development boards support the industry grade deployment

of IoT product and solution with higher duty cycle

applications. The key is the reliablity and extensive support

for programmablity. In this review a higest reliability index

of 10 has been given to above three Cypress and Microchip

platfroms.As these boards offer more reliabilty and higher

grade product development support hence the cost of these

devices are significatly higher. One more key point to be

highlighted here that all the above discussed development

platfrom works on bare metal environment.

Finally in this review we have discussed in section 2

about three MPU based boards, which is of a another

segment altogether. These boards have support for a full

fledged Linux based OS and are having a extensive features

like rich application support. The three boards we have

discussed in this category are Intel® Galileo Gen2, Texas

Instruments Beaglebone Black and Raspberry Pi 3. Intel®

Galileo Gen2 is powered by an Intel® Quark SoC x1000 400

MHz 256 MB DDR3 RAM. TI Beaglebone Black is having a

1 GHz ARM Cortex-A8 core with PowerVR SGX 2D/3D

graphics processor with 512 MB LPDDR RAM. Raspberry

Pi 3 is powered by a Broadcom BCM2837 quad core ARM

Cortex-A53, 1.2GHz with a GPU of VideoCoreIV and 1 GB

LPDDR2 RAM. All these platform support Linux based OS.

As far as the technical specification is concerned Raspberry

Pi 3 is a sure winner and surprisingly the cost is lowest

around $35 however Intel® Galileo Gen2 costing around $58

and TI board is near about $65. This is a clear indicator why

the Raspberry Pi is so popular among product and application

developers around the globe.

ACKNOWLEDGMENTS

All the development boards are evaluated and tested in

Wireless Communication and Networking Lab, School of

Electronics Engineering, KIIT Deemed to be University.

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